I am an AI and Machine Learning Engineer with practical experience in developing data-driven applications, generative AI solutions, and machine learning models. I combine hands-on technical implementation with an understanding of business processes and user needs.
I translate domain requirements into reliable applications and critically evaluate their outcomes. My work includes data preparation, model development, API integration, deployment, monitoring, and technical documentation.
During my AI development internship, I built a bilingual RAG chatbot for a public-sector use case, taking it from requirements gathering through production operation. I also improved response quality using real user queries and supported interns through code reviews, testing, and documentation.
Previously, I worked as a Data Analyst in the insurance domain, where I analyzed claims data, developed fraud detection and contract renewal models, and communicated insights through Power BI dashboards. I am experienced in turning model results into actionable information for business stakeholders.
I have a Master of Science in Applied Data Science and Analytics and hold certifications in deep learning and Azure data engineering. I am particularly interested in AI applications for forecasting, intelligent assistants, document automation, and process optimization.
Developed a bilingual German and English RAG chatbot for the city of Bad Breisig using Python, LangChain, and ChromaDB. Delivered the solution from requirements gathering through production operation, including frontend integration through REST APIs.
Improved chatbot response quality after launch by analyzing real user questions and implementing targeted adjustments. Supported two interns with code reviews, testing, and technical documentation.
Cleaned and analyzed insurance and claims data from the Majesco system using Python and SQL. Assessed missing values, duplicate records, and data discrepancies to establish reliable datasets for analytical and machine learning work.
Developed and validated Random Forest models for potential fraud detection and Gradient Boosting models for contract renewal prediction. Created Power BI dashboards for fraud risks and renewal trends, presented findings to business teams, and proposed follow-up analyses and reviews.
Master of Science, Applied Data Science and Analytics
Bachelor of Engineering, Computer Science and Engineering
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